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Implement analyses that use data science to understand and map the relationships between climate, conflict, migration, and peace, with a geographically-explicit focus. These analyses will tap into large databases of climate, agriculture, migration, and conflict, and use innovative methods to explore this complex problem.
Develop methods that to support risk modelling and projection based on climatic and socio-economic data.
Use analytical skills to support the implementation of national and local-level analyses that feed into the Climate Security Observatory. This will include agriculture and conflict risk analysis, and model-based climate impact and adaptation assessments in the areas (countries, regions) of interest to the Alliance and its partners.
Automate and document analytical routines and contribute to capacity development of partners as needed.
Contribute to the writing of high-quality technical notes, project reports, and if of interest also peer- reviewed publications.
Work collaboratively with the rest of the Climate Security team to develop a deep understanding of the relationships between climate and conflict. The team uses a wide array of approaches spanning the social and natural sciences, and the challenge is to integrate data science approaches with other approaches used by the team.
Stay up to date with the most recent literature on spatial data science, climate and conflict, climate impacts, adaptation, sustainable agriculture, food systems modelling, and climate risk assessment.
Contribute to project proposal writing and bilateral fundraising.
Other tasks as assigned as relevant to expertise and ongoing or future projects.
Ensuring that risks management are considered in the delivery of the assigned duties and responsibilities.
Requirements
MSc degree in agricultural science, data science, environmental science, geography, geoinformatics, geospatial, geomatics, with an understanding of climate-related risks, climate impacts, and adaptation in agriculture, and an interest in modelling complex problems.
Experience working with conflict/peace and linkages to migration is a plus.
Proven experience with spatial analysis, and handling of large geospatial datasets using R and/or Python is a must.
Familiarity with Google Earth Engine a plus.
Experience with collaborative algorithm development.
Strong familiarity and experience working with large geospatial climate datasets including climate model outputs (e.g., CMIP5/6), historical climate data (e.g., station data, CHIRPS, CHIRTS), and agricultural datasets such as crop yield data, soils data, etc.
Experience with modelling and forecasting yields, climatic and/or environmental systems.
Experience in the use of remote sensing data is a plus.
Specific experience with machine learning approaches, and spatial statistics is a requirement, as is experience handling large databases for modelling and data analysis.
Excellent/proven English writing skills. Other languages (e.g., French, English, local languages) would be a plus.
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